Effects of Metabolizable Energy Intake and Body-Weight Restriction on Layer Pullets: 1-Growth, Uniformity, and Efficiency
Bibliographic record
Abstract
This study aimed to determine the effects of dietary energy and body-weight (BW) restriction on layer pullets’ growth, uniformity, and feed efficiency. Two experiments were conducted using a precision feeding (PF) system (Experiment 1) and a conventional feeding (CON) system (Experiment 2). Experiment 1 consisted of a 2 × 4 factorial arrangement (eight treatments) with two feed allocation (FA) levels: meal every visit (MEV) or restricted to the lower boundary of Lohmann Brown-Lite pullets; and three dietary metabolizable energy (ME) levels: Low, Standard (Std), and High (2600, 2800, and 3000 kcal/kg, respectively); the fourth treatment enabled birds to choose from the three diets (Choice). Experiment 2 consisted of a 2 × 3 factorial arrangement (six treatments): two FA levels (ad libitum or restricted) and three dietary ME levels (Low, Std, and High). In each experiment, BW, coefficient of variation (CV), average daily feed intake (ADFI), average daily metabolizable energy intake (MEI), and feed conversion ratio (FCR) were recorded. Diet ADFI preferences and feeding motivation were determined only in the PF experiment. ANOVA was conducted on each experiment with the two main effects as fixed factors (FA and dietary ME), and age or period as the sources of variation. Differences were reported at p ≤ 0.05. MEV (PF experiment) and ad libitum-fed (CON experiment) pullets had greater BW compared to restricted-fed pullets (p < 0.05). The lowest CV was observed in the restricted-fed pullets from the PF experiment (p < 0.05). ADFI was greater in pullets fed the Low ME diet in the PF experiment compared to all the other groups, and the lower the dietary ME, the greater the ADFI in the CON experiment (p < 0.05). Choice-feeding pullets preferred feed with greater ME content in the PF experiment (p < 0.05). The lower the dietary ME, the greater the FCR in the CON experiment (p < 0.05). Restricted-fed pullets had greater daily visits, and lower daily meals, meal size, and successful visits to the PF system (p < 0.05). In conclusion, the results of this trial indicated that lower dietary ME increased FCR and ADFI, whereas feed restriction decreased BW and increased feeding motivation. Future steps after this trial will include examining the effects of dietary energy and feed restriction on carcass composition and sexual maturation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".